import pandas as pd
import matplotlib.pyplot as plt
from pandas import ExcelWriter
import os
import numpy as np
import random
plt.style.use("seaborn")
Parameters = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Modelling/HealthySamples.xlsx")
Parameters
count = 1
for i in range(0, len(Parameters)):
if Parameters.loc[i][10] == "Perfect":
data = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Healthy/Samples/" + Parameters.loc[i][2][:-4] + "/" + Parameters.loc[i][2][:-4] + "_" + str(Parameters.loc[i][1]) + ".xlsx")
data.Time = pd.to_numeric(data.Time, errors='coerce')
data.Sensor1 = pd.to_numeric(data.Sensor1, errors='coerce')
data.Sensor2 = pd.to_numeric(data.Sensor2, errors='coerce')
data.Sensor3 = pd.to_numeric(data.Sensor3, errors='coerce')
data.index = data.Time
ax = data.plot.line(x='Time', y=["Sensor1", "Sensor2", "Sensor3"],figsize = (15, 8 ))
b = data[data["Sensor1"] == Parameters.loc[i][3]]
c = data[data["Sensor2"] == Parameters.loc[i][4]]
d = data[data["Sensor3"] == Parameters.loc[i][5]]
fro = data[data["Sensor3"] == data.loc[Parameters.loc[i][7]][4]]
to = data[data["Sensor3"] == data.loc[Parameters.loc[i][8]][4]]
b.plot.scatter(x="Time", y="Sensor1", ax=ax,color="r", marker="o",s=50)
c.plot.scatter(x="Time", y="Sensor2", ax=ax,color="r", marker="o",s=50)
d.plot.scatter(x="Time", y="Sensor3", ax=ax,color="r", marker="o",s=50)
fro.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
to.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
print("Sample: ",count)
plt.show()
count = count + 1
else:
pass
Parameters = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Modelling/UnHealthySamples.xlsx")
Parameters
count = 1
for i in range(0, len(Parameters)):
if Parameters.loc[i][10] == "Perfect":
data = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Unhealthy/Samples/" + Parameters.loc[i][2][:-4] + "/" + Parameters.loc[i][2][:-4] + "_" + str(Parameters.loc[i][1]) + ".xlsx")
data.Time = pd.to_numeric(data.Time, errors='coerce')
data.Sensor1 = pd.to_numeric(data.Sensor1, errors='coerce')
data.Sensor2 = pd.to_numeric(data.Sensor2, errors='coerce')
data.Sensor3 = pd.to_numeric(data.Sensor3, errors='coerce')
data.index = data.Time
ax = data.plot.line(x='Time', y=["Sensor1", "Sensor2", "Sensor3"],figsize = (15, 8 ))
b = data[data["Sensor1"] == Parameters.loc[i][3]]
c = data[data["Sensor2"] == Parameters.loc[i][4]]
d = data[data["Sensor3"] == Parameters.loc[i][5]]
fro = data[data["Sensor3"] == data.loc[Parameters.loc[i][7]][4]]
to = data[data["Sensor3"] == data.loc[Parameters.loc[i][8]][4]]
b.plot.scatter(x="Time", y="Sensor1", ax=ax,color="r", marker="o",s=50)
c.plot.scatter(x="Time", y="Sensor2", ax=ax,color="r", marker="o",s=50)
d.plot.scatter(x="Time", y="Sensor3", ax=ax,color="r", marker="o",s=50)
fro.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
to.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
print("Sample: ", count)
plt.show()
count = count + 1
else:
pass